State-of-the-art deepfake detectors perform well in identifying forgeries when they are
evaluated on a test set similar to the training set, but struggle to maintain good performance …

In recent years, as various realistic face forgery techniques known as DeepFake improves
by leaps and bounds, more and more DeepFake detection techniques have been proposed …

Sparse-view computed tomography (CT)---using a small number of projections for
tomographic reconstruction---enables much lower radiation dose to patients and …

Image manipulation techniques have drawn growing concerns as manipulated images
might cause morality and security problems. Various methods have been proposed to detect …

Deepfake or synthetic images produced using deep generative models pose serious risks to
online platforms. This has triggered several research efforts to accurately detect deepfake …

Deep Metric Learning (DML) is very effective for many computer vision applications such as
image retrieval or cross-modal matching. The common paradigm for DML is to seek metric …

With the rapid progress over the past five years, face authentication has become the most
pervasive biometric recognition method. Thanks to the high-accuracy recognition …

Adding perturbations via utilizing auxiliary gradient information or discarding existing details
of the benign images are two common approaches for generating adversarial examples …

The security of AI systems has gained significant attention in recent years, particularly in the
medical diagnosis field. To develop a secure medical image classification system based on …

In recent few years, DeepFakes are posing serve threats and concerns to both individuals
and celebrities, as realistic DeepFakes facilitate the spread of disinformation. Model …